Literatura académica sobre el tema "MITIGATION ALGORITHM"
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Artículos de revistas sobre el tema "MITIGATION ALGORITHM"
Ding, Yi, Weiwei Fan, Zijing Zhang, Feng Zhou y Bingbing Lu. "Radio Frequency Interference Mitigation for Synthetic Aperture Radar Based on the Time-Frequency Constraint Joint Low-Rank and Sparsity Properties". Remote Sensing 14, n.º 3 (7 de febrero de 2022): 775. http://dx.doi.org/10.3390/rs14030775.
Texto completoDhineshkumar, K. y C. Subramani. "Kalman Filter Algorithm for Mitigation of Power System Harmonics". International Journal of Electrical and Computer Engineering (IJECE) 8, n.º 2 (1 de abril de 2018): 771. http://dx.doi.org/10.11591/ijece.v8i2.pp771-779.
Texto completoMajumder, Swarnadeep, Christopher G. Yale, Titus D. Morris, Daniel S. Lobser, Ashlyn D. Burch, Matthew N. H. Chow, Melissa C. Revelle, Susan M. Clark y Raphael C. Pooser. "Characterizing and mitigating coherent errors in a trapped ion quantum processor using hidden inverses". Quantum 7 (15 de mayo de 2023): 1006. http://dx.doi.org/10.22331/q-2023-05-15-1006.
Texto completoYousif, Tasneem y Paul Blunt. "Interference Mitigation for GNSS Receivers Using FFT Excision Filtering Implemented on an FPGA". Eng 3, n.º 4 (31 de octubre de 2022): 439–66. http://dx.doi.org/10.3390/eng3040032.
Texto completoSánchez-Cartas, Juan Manuel, Alberto Tejero y Gonzalo León. "Algorithmic Pricing and Price Gouging. Consequences of High-Impact, Low Probability Events". Sustainability 13, n.º 5 (26 de febrero de 2021): 2542. http://dx.doi.org/10.3390/su13052542.
Texto completoAhmed, Mohamed y Ezz Eldin Abdelkawy. "GPS correlated jammer mitigation utilizing MUSIC algorithm". International Conference on Electrical Engineering 7, n.º 7 (1 de mayo de 2010): 1–10. http://dx.doi.org/10.21608/iceeng.2010.33043.
Texto completoVU, Trung Kien, Sungoh KWON y Sangchul OH. "Cooperative Interference Mitigation Algorithm in Heterogeneous Networks". IEICE Transactions on Communications E98.B, n.º 11 (2015): 2238–47. http://dx.doi.org/10.1587/transcom.e98.b.2238.
Texto completoAkanji, Oluwatobi Shadrach, Opeyemi Aderiike Abisoye y Mohammed Awwal Iliyasu. "MITIGATING SLOW HYPERTEXT TRANSFER PROTOCOL DISTRIBUTED DENIAL OF SERVICE ATTACKS IN SOFTWARE DEFINED NETWORKS". Journal of Information and Communication Technology 20, Number 3 (11 de junio de 2021): 277–304. http://dx.doi.org/10.32890/jict2021.20.3.1.
Texto completoSHIN, J. H., J. HEO, S. YOON y S. Y. KIM. "Interference Cancellation and Multipath Mitigation Algorithm for GPS Using Subspace Projection Algorithms". IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences E91-A, n.º 3 (1 de marzo de 2008): 905–8. http://dx.doi.org/10.1093/ietfec/e91-a.3.905.
Texto completoGarzia, Fabio, Johannes Rossouw van der Merwe, Alexander Rügamer, Santiago Urquijo y Wolfgang Felber. "HDDM Hardware Evaluation for Robust Interference Mitigation". Sensors 20, n.º 22 (13 de noviembre de 2020): 6492. http://dx.doi.org/10.3390/s20226492.
Texto completoTesis sobre el tema "MITIGATION ALGORITHM"
Zubi, Hazem M. "A genetic algorithm approach for three-phase harmonic mitigation filter design". Thesis, University of Bath, 2013. https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.604881.
Texto completoIkuma, Takeshi. "Non-Wiener Effects in Narrowband Interference Mitigation Using Adaptive Transversal Equalizers". Diss., Virginia Tech, 2007. http://hdl.handle.net/10919/26772.
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Manmek, Thip Electrical Engineering & Telecommunications Faculty of Engineering UNSW. "Real-time power system disturbance identification and its mitigation using an enhanced least squares algorithm". Awarded by:University of New South Wales. Electrical Engineering and Telecommunications, 2006. http://handle.unsw.edu.au/1959.4/26233.
Texto completoGandhi, Nikhil Tej. "Automatic Dependent Surveillance - Broadcast Enabled, Wake Vortex Mitigation Using Cockpit Display". Ohio University / OhioLINK, 2012. http://rave.ohiolink.edu/etdc/view?acc_num=ohiou1354313600.
Texto completoLoh, Nolan. "Buildings as urban climate infrastructure: A framework for designing building forms and facades that mitigate urban heat". University of Cincinnati / OhioLINK, 2019. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1553513750865168.
Texto completoAl-Odat, Zeyad Abdel-Hameed. "Analyses, Mitigation and Applications of Secure Hash Algorithms". Diss., North Dakota State University, 2020. https://hdl.handle.net/10365/32058.
Texto completoKivrikis, Andreas y Johan Tjernström. "Development and Evaluation of Multiple Objects Collision Mitigation by Braking Algorithms". Thesis, Linköping University, Department of Electrical Engineering, 2004. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-2676.
Texto completoA CMbB system is a system that with the help of sensors in the front of a car detects when a collision in unavoidable. When a situation like that is detected, the brakes are activated. The decision of whether to activate the brakes or not is taken by a piece of software called a decision maker. This software continuously checks for routes that would avoid an object in front of the car and as long as a path is found nothing is done. Volvo has been investigating several different CMbB-systems, and the research done by Volvo has previously focused on decision makers that only consider one object in front of the car. By instead taking all present objects in consideration, it should be possible to detect an imminent collision earlier. Volvo has developed some prototypes but needed help evaluating their performance.
As part of this thesis a testing method was developed. The idea was to test as many cases as possible but as the objects’ possible states increase, the number of test cases quickly becomes huge. Different ways of removing irrelevant test cases were developed and when these ideas were realized in a test bench, it showed that about 98 % of the test cases could be removed.
The test results showed that there is clearly an advantage to consider many objects if the cost of increased complexity in the decision maker is not too big. However, the risk of false alarms is high with the current decision makers and several possible improvements have therefore been suggested.
Santos, Fernando Fernandes dos. "Reliability evaluation and error mitigation in pedestrian detection algorithms for embedded GPUs". reponame:Biblioteca Digital de Teses e Dissertações da UFRGS, 2017. http://hdl.handle.net/10183/159210.
Texto completoPedestrian detection reliability is a fundamental problem for autonomous or aided driving. Methods that use object detection algorithms such as Histogram of Oriented Gradients (HOG) or Convolutional Neural Networks (CNN) are today very popular in automotive applications. Embedded Graphics Processing Units (GPUs) are exploited to make object detection in a very efficient manner. Unfortunately, GPUs architecture has been shown to be particularly vulnerable to radiation-induced failures. This work presents an experimental evaluation and analytical study of the reliability of two types of object detection algorithms: HOG and CNNs. This research aim is not just to quantify but also to qualify the radiation-induced errors on object detection applications executed in embedded GPUs. HOG experimental results were obtained using two different architectures of embedded GPUs (Tegra and AMD APU), each exposed for about 100 hours to a controlled neutron beam at Los Alamos National Lab (LANL). Precision and Recall metrics are considered to evaluate the error criticality. The reported analysis shows that, while being intrinsically resilient (65% to 85% of output errors only slightly impact detection), HOG experienced some particularly critical errors that could result in undetected pedestrians or unnecessary vehicle stops. This works also evaluates the reliability of two Convolutional Neural Networks for object detection: You Only Look Once (YOLO) and Faster RCNN. Three different GPU architectures were exposed to controlled neutron beams (Kepler, Maxwell, and Pascal) detecting objects in both Caltech and Visual Object Classes data sets. By analyzing the neural network corrupted output, it is possible to distinguish between tolerable errors and critical errors, i.e., errors that could impact detection. Additionally, extensive GDB-level and architectural-level fault-injection campaigns were performed to identify HOG and YOLO critical procedures. Results show that not all stages of object detection algorithms are critical to the final classification reliability. Thanks to the fault injection analysis it is possible to identify HOG and Darknet portions that, if hardened, are more likely to increase reliability without introducing unnecessary overhead. The proposed HOG hardening strategy is able to detect up to 70% of errors with a 12% execution time overhead.
Salomon, Sophie. "Bias Mitigation Techniques and a Cost-Aware Framework for Boosted Ranking Algorithms". Case Western Reserve University School of Graduate Studies / OhioLINK, 2020. http://rave.ohiolink.edu/etdc/view?acc_num=case1586450345426827.
Texto completoBhattacharya, Koustav. "Architectures and algorithms for mitigation of soft errors in nanoscale VLSI circuits". [Tampa, Fla] : University of South Florida, 2009. http://purl.fcla.edu/usf/dc/et/SFE0003280.
Texto completoLibros sobre el tema "MITIGATION ALGORITHM"
Casola, Linda y Dionna Ali, eds. Robust Machine Learning Algorithms and Systems for Detection and Mitigation of Adversarial Attacks and Anomalies. Washington, D.C.: National Academies Press, 2019. http://dx.doi.org/10.17226/25534.
Texto completoWu, Jinsong, Sundeep Rangan y Honggang Zhang. Green Communications: Theoretical Fundamentals, Algorithms and Applications. Taylor & Francis Group, 2016.
Buscar texto completoComputer Science and Telecommunications Board, National Academies of Sciences, Engineering, and Medicine, Division on Engineering and Physical Sciences, Intelligence Community Studies Board y Board on Mathematical Sciences and Analytics. Robust Machine Learning Algorithms and Systems for Detection and Mitigation of Adversarial Attacks and Anomalies: Proceedings of a Workshop. National Academies Press, 2019.
Buscar texto completoNational Academies of Sciences, Engineering, and Medicine. Robust Machine Learning Algorithms and Systems for Detection and Mitigation of Adversarial Attacks and Anomalies: Proceedings of a Workshop. National Academies Press, 2019.
Buscar texto completoComputer Science and Telecommunications Board, National Academies of Sciences, Engineering, and Medicine, Division on Engineering and Physical Sciences, Intelligence Community Studies Board y Board on Mathematical Sciences and Analytics. Robust Machine Learning Algorithms and Systems for Detection and Mitigation of Adversarial Attacks and Anomalies: Proceedings of a Workshop. National Academies Press, 2019.
Buscar texto completoWu, Jinsong, Sundeep Rangan y Honggang Zhang. Green Communications: Theoretical Fundamentals, Algorithms, and Applications. Taylor & Francis Group, 2016.
Buscar texto completoWu, Jinsong, Sundeep Rangan y Honggang Zhang. Green Communications: Theoretical Fundamentals, Algorithms, and Applications. Taylor & Francis Group, 2016.
Buscar texto completoWu, Jinsong, Sundeep Rangan y Honggang Zhang. Green Communications: Theoretical Fundamentals, Algorithms, and Applications. Taylor & Francis Group, 2016.
Buscar texto completoWu, Jinsong, Sundeep Rangan y Honggang Zhang. Green Communications: Theoretical Fundamentals, Algorithms, and Applications. Taylor & Francis Group, 2016.
Buscar texto completoGreen Communications: Theoretical Fundamentals, Algorithms and Applications. Taylor & Francis Group, 2012.
Buscar texto completoCapítulos de libros sobre el tema "MITIGATION ALGORITHM"
Zhu, Xuanzhang. "A Novel NLOS Mitigation Algorithm Using VBS". En Lecture Notes in Electrical Engineering, 209–17. Berlin, Heidelberg: Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-40633-1_27.
Texto completoÁdám, Zsófia, Levente Bajczi, Mihály Dobos-Kovács, Ákos Hajdu y Vince Molnár. "Theta: portfolio of CEGAR-based analyses with dynamic algorithm selection (Competition Contribution)". En Tools and Algorithms for the Construction and Analysis of Systems, 474–78. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-99527-0_34.
Texto completoHu, Yang, Zhongliang Deng, Jichao Jiao, Jie Xia, Yuezhou Hu y Zhuang Yuan. "Cross Correlation Mitigation Algorithm for Indoor Positioning Receiver". En Lecture Notes in Electrical Engineering, 485–92. Berlin, Heidelberg: Springer Berlin Heidelberg, 2015. http://dx.doi.org/10.1007/978-3-662-46632-2_42.
Texto completoRay, Papia y Surender Reddy Salkuti. "Short-Term Load Forecasting Using Jaya Algorithm". En Power Quality in Microgrids: Issues, Challenges and Mitigation Techniques, 315–42. Singapore: Springer Nature Singapore, 2023. http://dx.doi.org/10.1007/978-981-99-2066-2_15.
Texto completoShi, Sheng, Shanshan Wei, Zhongchao Shi, Yangzhou Du, Wei Fan, Jianping Fan, Yolanda Conyers y Feiyu Xu. "Algorithm Bias Detection and Mitigation in Lenovo Face Recognition Engine". En Natural Language Processing and Chinese Computing, 442–53. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-60457-8_36.
Texto completoLi, Jie, Yuliang Li y Yingwu Zhou. "GPS Multipath Mitigation Algorithm Using C/A Code Correlation Character". En The Proceedings of the Second International Conference on Communications, Signal Processing, and Systems, 1047–58. Cham: Springer International Publishing, 2013. http://dx.doi.org/10.1007/978-3-319-00536-2_121.
Texto completoNamrata, Kumari, Nishant Kumar, Ch Sekhar, Ramjee Prasad Gupta y Surender Reddy Salkuti. "Modeling and Sizing of the Hybrid Renewable System Opting Genetic Algorithm". En Power Quality in Microgrids: Issues, Challenges and Mitigation Techniques, 535–63. Singapore: Springer Nature Singapore, 2023. http://dx.doi.org/10.1007/978-981-99-2066-2_25.
Texto completoChen, Lei, Shuai Han, Weixiao Meng y Zijun Gong. "A Spoofing Mitigation Algorithm Based on Subspace Projection for GNSS Receiver". En China Satellite Navigation Conference (CSNC) 2015 Proceedings: Volume I, 727–37. Berlin, Heidelberg: Springer Berlin Heidelberg, 2015. http://dx.doi.org/10.1007/978-3-662-46638-4_63.
Texto completoMallala, Balasubbareddy, P. Venkata Prasad y Kowstubha Palle. "Analysis of Power Quality Issues and Mitigation Techniques Using HACO Algorithm". En Intelligent Sustainable Systems, 841–51. Singapore: Springer Nature Singapore, 2023. http://dx.doi.org/10.1007/978-981-99-1726-6_65.
Texto completoMinango, Juan, Marcelo Zambrano y Jorge Caraguay. "Co-channel Interference Mitigation Using Convolutional Enconder via Joint Decoding Viterbi Algorithm". En Innovation and Research - A Driving Force for Socio-Econo-Technological Development, 11–21. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-11438-0_2.
Texto completoActas de conferencias sobre el tema "MITIGATION ALGORITHM"
Meng, Dawei, Zhenming Feng y Mingquan Lu. "HOS-Based Interference Mitigation Algorithm". En Multiconference on "Computational Engineering in Systems Applications. IEEE, 2006. http://dx.doi.org/10.1109/cesa.2006.4281616.
Texto completoLeonid, T. Thomas, Harish Kanna, Claudia Christy V J, Hamritha A S y Chebolu Lokesh. "Human Wildlife Conflict Mitigation Using YOLO Algorithm". En 2023 Eighth International Conference on Science Technology Engineering and Mathematics (ICONSTEM). IEEE, 2023. http://dx.doi.org/10.1109/iconstem56934.2023.10142629.
Texto completoHo, M. T., H. A. Krichene, G. F. Ricciardi y W. J. Geckle. "Multipath mitigation in calibration range estimation algorithm". En 2017 IEEE Radar Conference (RadarConf17). IEEE, 2017. http://dx.doi.org/10.1109/radar.2017.7944397.
Texto completoMostefa, Mohammed Belhadj, Abdelfettah Boussaid y Abdelmalek Khezzar. "FPGA-based Algorithm for Harmonic Current Mitigation". En 2022 2nd International Conference on Advanced Electrical Engineering (ICAEE). IEEE, 2022. http://dx.doi.org/10.1109/icaee53772.2022.9962021.
Texto completoConcatto, Fernando, Wellington Zunino, Luigi A. Giancoli, Rafael Santiago y Luís C. Lamb. "Genetic algorithm for epidemic mitigation by removing relationships". En GECCO '17: Genetic and Evolutionary Computation Conference. New York, NY, USA: ACM, 2017. http://dx.doi.org/10.1145/3071178.3071218.
Texto completoPeng, Xiaohui, Fei Hu, Feng He, Liang Wu, Jun Li, Dong Zhu, Zhiqiang Liao y Cuifang Qian. "RFI mitigation of SMOS image based on CLEAN algorithm". En IGARSS 2016 - 2016 IEEE International Geoscience and Remote Sensing Symposium. IEEE, 2016. http://dx.doi.org/10.1109/igarss.2016.7729206.
Texto completoSu, Y. Q., Y. L. Yang, Y. T. Mi y X. F. Yin. "Multipath mitigation method of GPS signals utilizing SAGE algorithm". En 2012 International Conference on System Simulation (ICUSS 2012). IET, 2012. http://dx.doi.org/10.1049/cp.2012.0561.
Texto completoHoshida, Takeshi, Liang Dou, Weizhen Yan, Lei Li, Zhenning Tao, Shoichiro Oda, Hisao Nakashima, Chihiro Ohshima, Tomofumi Oyama y Jens C. Rasmussen. "Advanced and Feasible Signal Processing Algorithm for Nonlinear Mitigation". En Optical Fiber Communication Conference. Washington, D.C.: OSA, 2013. http://dx.doi.org/10.1364/ofc.2013.oth3c.3.
Texto completoBhagwat, N., K. Liu y B. Jabbari. "Robust Bias Mitigation Algorithm for Localization in Wireless Networks". En ICC 2010 - 2010 IEEE International Conference on Communications. IEEE, 2010. http://dx.doi.org/10.1109/icc.2010.5501752.
Texto completoPardhasaradhi, Bethi, Gunnery Srinath, Ashoka Chakravarthi Mahipathi, Pathipati Srihari y Linga Reddy Cenkeramaddi. "A GNSS Position Spoofing Mitigation Algorithm using Sparse Estimation". En 2022 IEEE 19th India Council International Conference (INDICON). IEEE, 2022. http://dx.doi.org/10.1109/indicon56171.2022.10039936.
Texto completoInformes sobre el tema "MITIGATION ALGORITHM"
Visser, R., H. Kao, R. M. H. Dokht, A. B. Mahani y S. Venables. A comprehensive earthquake catalogue for northeastern British Columbia: the northern Montney trend from 2017 to 2020 and the Kiskatinaw Seismic Monitoring and Mitigation Area from 2019 to 2020. Natural Resources Canada/CMSS/Information Management, 2021. http://dx.doi.org/10.4095/329078.
Texto completoPound, B. G. GRI-99-0000 Gap Analysis of the GRI Research Program on Internal Corrosion. Chantilly, Virginia: Pipeline Research Council International, Inc. (PRCI), diciembre de 1999. http://dx.doi.org/10.55274/r0010720.
Texto completoLillard, Scott. DTPH56-15-H-CAP02 Understanding and Mitigating the Threat of AC Induced Corrosion on Buried Pipelines. Chantilly, Virginia: Pipeline Research Council International, Inc. (PRCI), enero de 2017. http://dx.doi.org/10.55274/r0011875.
Texto completoLi, Baisong y Bo Xu. PR-469-19604-Z01 Auto Diagnostic Method Development for Ultrasonic Flow Meter. Chantilly, Virginia: Pipeline Research Council International, Inc. (PRCI), febrero de 2022. http://dx.doi.org/10.55274/r0012204.
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